Measurement-based Statistical Method for Estimating and Verifying Signal Coverage and Coverage Probability in Urban Microcells

Joseph Isabona, Kingsley Obahiagbon

Abstract


Customer’s complaints and concerns about radio signal coverage at their home are important trigger to performance relevant drive test in the relevant area to observe the coverage quality. In this paper, statistical approach has been employed to assess the quality of the radio coverage and outage probability based on measured radio signals in an established UMTS network, operational in Ikoyi, a typical urban microcell in Nigerian environment. The results shows that the quality of radio signals at the cell edge is very poor in locations 2 and 4, as they recorded poor coverage probability performance of 89.25% and 81.72% and high outage probability performance of 10.74% and 18.28% respectively. It is also observed that the smaller the fade margin, the higher the outage probability and the lower the coverage reliability. This implies that the smaller the fade margin, the smaller the received signal strength at the MS and the more likely outage events. Hence, sufficient signal strength is needed at the mobile terminals at locations 2 and 4 in order to achieve the outage probability and coverage reliability required to effectively operate cellular communication networks.

Full Text:

PDF

References


T. Tonteri; A Statistical Modeling Approach to Location Estimation Helsinki, Master's Thesis Department of Computer Science, Faculty of Science, University of Helsinki, 2001.

https://en.wikipedia.org/wiki/GSM, accessed 13/12/2015.

S. Bouzouki, J.Panaoutsopoulos, C. Ioannous, S. Kotsopoulos and C.Soras; Coverage Probability Verification for Cells in Urban Radio Networks Planning, http://www.Scribd.com/doc/63488630/coverage-probability.

http://shodhganga.inflibnet.ac.in/bitstream/10603/1223/11/11_chapter%202.pdf

P.Bernardin and T. ellis; Cell Radius Inaccuracy: A New Measure of Coverage Reliability IEEE Transactions on Vehicular Technology, Vol. 47, No.4, pp. 1215-1226, 1998.

J. Isabona, and Peter I. G. Benchmarking Mobile Network Quality of Service with Essential Key Performance Indicators: A Case Study of Operational GSM Telecom Operators in Nigeria. Conference Proceedings of Nigerian Institute of Physics, 2014.

J. Isabona, Maximising Coverage and Capacity with QOS Guarantee in GSM Network by Means of Cell Cluster Optimization, International Journal of Advanced Research in Physical Science (IJARPS) Vol. 1, Issue 6, pp. 44-55, Oct. 2014.

3GPP TR 36.806 V9.0.0 (2009-12)

D. Kotz, C, Newport, R. Gray, J, Liu, Y, Yuan, andC, Elliott, Experimental Evaluation of Wireless Simulation Assumptions. In Proc. the 7th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems (MSWiM’04), Venice, Italy, pp. 78–82.Oct. 2004;

T. Rappaport, Wireless Communications: Principles and Practice, 2nd ed.; Prentice Hall PTR: Indianapolis, IN, USA, 2001.

T, Stoyanova, F, Kerasiotis, A, Prayati, A and G, Papadopoulos, A practical RF Propagation model for Wireless Network Sensors, Third international Conference on Sensor Technology and Applications, IEEE Computer Society, 2009.

The Network Simulator: ns-2. Available online:http://isi.edu/nsnam/ns/.

Kim, J, Kim, S and Choi K (2009) A New RBC handover scheme for LTE-R system, Journal of International Council on Electrical Engineering, vol. 4, No.3, pp. 243-250

J. Isabona and C.C. Konyeha; Urban Area Path loss Propagation Prediction and Optimisation Using Hata Model at 800MHz Journal of Applied Physics (IOSR-JAP), Vol.3, (4), pp. 08-18, 2013.

J. Isabona, C. C. Konyeha, C. B. Chinule. and I.G. Peter Radio Field Strength Propagation Data and Pathloss calculation Methods in UMTS Network, Advances in Physics Theories and Applications, vol. 21, pp. 54-68, 2013.

C. Umit Bas and S.C. Ergen; Spatial-temporal Characteristics of Link Quality in Wireless Sensor networks, IEEE wireless Communication and Networking conference (WCNC) pp. 1152-1152, 2012.

T.I,Adebayoand F.O, Edeko, Characterization of Propagation path loss at 1.8GHz: A case Study of Benin City, Nigeria. Research, Journal of Applied Sciences, vol. 1 (1-4), PP. 92-96, 2006.

Rautiainen,T, Varying Path loss and Delay Spread predictions of a 3D ray tracing Propagation model in Urban Environment. Institute of Electrical and Electronics Engineers (IEEE), 2001.

W.C.Y, Lee,Mobile Communication Design Fundamentals, 2nd Edition, John Wiley and Sons: New York, 1992.

S.Savas, N, Topaloglu, and B, Ciylan, B Analysis of Mobile Communication Signals with Frequency Analysis Method, Gazi University Journal of Science, vol. 25(2), PP.447-454, 2012.




DOI: https://doi.org/10.23956/ijarcsse.v8i6.724

Refbacks

  • There are currently no refbacks.




© International Journals of Advanced Research in Computer Science and Software Engineering (IJARCSSE)| All Rights Reserved | Powered by Advance Academic Publisher.